Lead AI / ML Data Scientist

At Nielsen, we are passionate about our work to power a better media future for all people by providing powerful insights that drive client decisions and deliver extraordinary results. Our talented, global workforce is dedicated to capturing audience engagement with content - wherever and whenever it’s consumed. Together, we are proudly rooted in our deep legacy as we stand at the forefront of the media revolution. When you join Nielsen, you will join a dynamic team committed to excellence, perseverance, and the ambition to make an impact together. We champion you, because when you succeed, we do too. We enable your best to power our future.

At Nielsen, we are seeking a Data Scientist to join our team. Are you passionate about pushing the boundaries with the latest advancements in AI/ML? Does the prospect of applying cutting-edge AI research to develop industry-defining software solutions for audience measurement excite you? In this role, you will be at the forefront of our mission, leveraging sophisticated machine learning and AI to deliver a comprehensive understanding of audience behavior. You will architect and implement AI/ML systems that unlock novel insights from complex audience data.

Core Responsibilities:

• Project Leadership: Take ownership of specific data science projects, guiding junior team members through the entire project lifecycle, from problem definition and data exploration to model deployment and evaluation.

• Solution Design & Development: Design and implement complex analytical solutions, including advanced machine learning models, statistical frameworks, and algorithmic approaches to address specific business problems in media and audience measurement.

• Mentorship & Knowledge Transfer: Actively mentor Data Scientists, providing technical guidance, code reviews, and best practices. Promote a culture of continuous learning and knowledge sharing within the team.

• Research & Innovation: Stay abreast of the latest advancements in data science and apply relevant techniques to improve existing models and develop innovative solutions. Conduct exploratory data analysis to uncover new insights.

• Collaboration: Work closely with Data Engineers to ensure data availability and quality, and with the Data Visualization Specialist to effectively communicate findings.

• Audience Segmentation & Profiling: Expertise in developing robust audience segments based on demographics, behaviors, interests, and consumption patterns across various media platforms.

• Content Optimization & Personalization: Strong background in analyzing content performance, identifying engagement drivers, and developing recommendation engines or personalization algorithms.

• Ad Effectiveness & Measurement: Proven ability to design and execute studies measuring the impact of advertising campaigns, including attribution modeling, lift analysis, and ROI calculation.

• Predictive Analytics & Forecasting: Experience in building predictive models for audience behavior, future trends, content virality, or advertising spend.

• Causal Inference: Deep understanding of experimental design (A/B testing, multivariate testing) and quasi-experimental methods to establish causality between interventions and outcomes.

• Advanced Programming & Modeling: Highly proficient in Python and/or R, with extensive experience in machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch), statistical modeling packages, and big data framework

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